Many existing computing systems include one or more traditional image capturing cameras as an integrated peripheral device. A current trend is to enhance computing system imaging capability by integrating depth capturing into its imaging components. Depth capturing may be used, for example, to perform various intelligent object recognition functions such as facial recognition (e.g., for secure system un-lock) or hand gesture recognition (e.g., for touchless user interface functions).
One depth information capturing approach, referred to as “time-of-flight” imaging, emits light from a system onto an object and measures, for each of multiple pixels of an image sensor, the time between the emission of the light and the reception of its reflected image upon the sensor. The image produced by the time of flight pixels corresponds to a three-dimensional profile of the object as characterized by a unique depth measurement (z) at each of the different (x,y) pixel locations.
As many computing systems with imaging capability are mobile in nature (e.g., laptop computers, tablet computers, smartphones, etc.), the integration of time-of-flight operation along with traditional image capture presents a number of design challenges such as cost challenges and packaging challenges.